Triple

T10310406
Position Surface form Disambiguated ID Type / Status
Subject Kemaman River E241871 entity
Predicate near P350 FINISHED
Object Kemaman town E855653 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Kemaman town | Statement: [Kemaman River, near, Kemaman town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kemaman town
Context triple: [Kemaman River, near, Kemaman town]
  • A. Kemaman District chosen
    Kemaman District is an administrative region in the state of Terengganu, Malaysia, known for its coastal towns, petroleum-based industries, and fishing activities along the South China Sea.
  • B. Kulim
    Kulim is a prominent town and industrial hub in the Malaysian state of Kedah, known for its high-tech manufacturing and proximity to Penang.
  • C. Kota Bharu
    Kota Bharu is a major city in northeastern Peninsular Malaysia known for its rich Malay culture, traditional markets, and role as the administrative and commercial center of Kelantan state.
  • D. Ratekau
    Ratekau is a municipality in the district of Ostholstein in Schleswig-Holstein, northern Germany, near the Baltic Sea coast.
  • E. Kuantan
    Kuantan is a coastal city on the east coast of Peninsular Malaysia known as a major economic and cultural center and gateway to the South China Sea.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d381ac38808190a8ca7457c85b625b completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d32a18ac81909b4efd8c1ba3e113 completed April 7, 2026, 9:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69d794ddbd9081909a534b29b3f75774 completed April 9, 2026, noon
Created at: April 6, 2026, 11:47 a.m.